1. Technical Field
The present disclosure relates to object recognition for objects bearing machine-readable symbols.
2. Description of the Related Art
Machine-readable symbols encode information in a form that can be optically read via an appropriately configured machine-readable symbol reader or scanner. Machine-readable symbols take a variety of forms, the most commonly recognized form being the linear or one-dimension barcode symbol. Other forms include two-dimensional machine-readable symbols such as stacked code symbols, and area or matrix code symbols. These machine-readable symbols are typically composed on patterns of high and low reflectance areas. For instance, a barcode symbol may comprise a pattern of black bars on a white background. Also for instance, a two-dimensional symbol may comprise a pattern of black marks (e.g., bars, squares or hexagons) on a white background. Machine-readable symbols are not limited to being black and white, but may comprise two other colors, and/or may include more than two colors (e.g., more than black and white).
Machine-readable symbols are typically composed of elements (e.g., symbol characters) which are selected from a particular machine-readable symbology. Information is encoded in the particular sequence of shapes (e.g., bars) and spaces which may have varying dimensions. The machine-readable symbology provides a mapping between machine-readable symbols or symbol characters and human-readable symbols (e.g., alpha, numeric, punctuation, commands). A large number of symbologies have been developed and are in use, for example Universal Product Code (UPC), European Article Number (EPN), Code 39, Code 128, Data Matrix, PDF417, etc.
Machine-readable symbols have widespread and varied applications. For example, machine-readable symbols can be used to identify a class of objects (e.g., merchandise) or unique objects (e.g., patents). As a result, machine-readable symbols are found on a wide variety of objects, such as retail goods, company assets, and documents, and help track production at manufacturing facilities and inventory at stores (e.g., by scanning objects as they arrive and as they are sold). In addition, machine-readable symbols may appear on a display of a portable electronic device, such as a mobile telephone, personal digital assistant, tablet computer, laptop computer, or other device having an electronic display. For example, a customer, such as a shopper, airline passenger, or person attending a sporting event or theater event, may cause a machine-readable symbol to be displayed on their portable electronic device so that an employee (e.g., merchant-employee) can read the machine-readable symbol via a machine-readable symbol reader to allow the customer to redeem a coupon or to verify that the customer has purchased a ticket for the event.
Machine-readable symbol readers or machine-readable symbol readers are used to capture images or representations of machine-readable symbols appearing on various surfaces to read the information encoded in the machine-readable symbol. One commonly used machine-readable symbol reader is an imager- or imaging-based machine-readable symbol reader. Imaging-based machine-readable symbol readers typically employ flood illumination to simultaneously illuminate the entire machine-readable symbol, either from dedicated light sources, or in some instances using ambient light. Such is in contrast to scanning or laser-based (i.e., flying spot) type machine-readable symbol readers, which scan a relative narrow beam or spot of light sequentially across the machine-readable symbol.
Imaging-based machine-readable symbol readers typically include solid-state image circuitry, such as charge-coupled devices (CCDs) or complementary metal-oxide semiconductor (CMOS) devices, and may be implemented using a one-dimensional or two-dimensional imaging array of photosensors (or pixels) to capture an image of the machine-readable symbol. One-dimensional CCD or CMOS readers capture a linear cross-section of the machine-readable symbol, producing an analog waveform whose amplitude represents the relative darkness and lightness of the machine-readable symbol. Two-dimensional CCD or CMOS readers may capture an entire two-dimensional image. The image is then processed to find and decode a machine-readable symbol. For example, virtual scan line techniques for digitally processing an image containing a machine-readable symbol sample across an image along a plurality of lines, typically spaced apart and at various angles, somewhat like a scan pattern of a laser beam in a scanning or laser-based scanner.
Machine-readable symbol readers may be generally classified into one of three types: manual readers, semi-automatic readers, and automated readers. With manual or semi-automatic readers (e.g., a hand-held type reader, or a fixed-position reader), a human operator positions an object relative to the view volume of the reader to read the machine-readable symbol associated with the object. In an automated reader (e.g., a portal or tunnel scanner), a conveyor automatically positions the object relative to the view volume, and transports the object through the view volume so that the reader can automatically read the machine-readable symbol associated with the object.
When a machine-readable symbol reader attempts to read a machine-readable symbol on an object, certain read errors may occur, or the reader may fail to read the machine-readable symbol. For example, when a read error or read failure occurs with a manual or semi-automatic reader, the reader may prompt the human operator to rescan the machine-readable symbol or to manually enter (e.g., via a keyboard) a number (e.g., a UPC number) corresponding to the object. In an automated reader, the reader needs to determine automatically whether an error or an unexpected event (i.e., “exception”) occurs and, if such an error or unexpected event occurs, take appropriate exception action. Accordingly, the present inventor has recognized a need to accurately identify and handle read errors or read failures and unexpected events that may occur in automated readers.